自然资源遥感2025，Vol.37Issue(2)：185-193,9.DOI:10.6046/zrzyyg.2023378
2000-2022年北京市植被春季物候期变化特征分析
Analysis of the changes in spring phenology of vegetation in Beijing City from 2000 to 2022
摘要
Abstract
Investigating spring phenology is critical for understanding the growth and development cycles of vegetation and the response mechanisms to climate and environmental changes.It also provides significant insights for guiding agricultural production and protecting and restoring ecosystems.This study reconstructed the time series of MOD13Q1 data for Beijing City from 2000 to 2022.Based on dynamic thresholding,this study extracted the spring phenology of vegetation in Beijing City over the past 23 years.Furthermore,this study analyzed the spatiotemporal changes in spring phenology in Beijing City using the Mann-Kendall(M-K)trend test.Finally,this study examined the differential responses of spring phenology to climate change through partial correlation analysis.The results of this study indicate that the average spring phenology of vegetation in Beijing City occurred on the 117th day of a year(in late April),advancing at an average rate of approximately 1.14 days per year over the past 23 years.Different duo exhibited distinct hierarchical variations in spring phenology.Forests showed the earliest spring phenology starting from the 107th day,followed by shrubs(the 117th day)and grasslands(the 119th day),with the latest being farmland(the 130th day).The impacts of average annual temperature on spring phenology exhibited significant spatial variations.A positive correlation was observed in water-rich areas such as rivers and reservoirs,whereas a significant negative correlation occurred in eastern Fangshan District.On a monthly scale,temperatures in November,December,January,and February significantly influenced spring phenology.As winter temperatures rose,the spring phenology of vegetation tended to advance.This study explores the response mechanisms of spring phenology of vegetation in Beijing City to temperature and precipitation,providing valuable insights for vegetation management under climate change.关键词
植被遥感物候/NDVI/时间序列重建Key words
remote sensing vegetation phenology/NDVI/time series reconstruction分类
信息技术与安全科学引用本文复制引用
谢宜嘉,杨倍倍,张镇,陈佳,王喆,孟令奎..2000-2022年北京市植被春季物候期变化特征分析[J].自然资源遥感,2025,37(2):185-193,9.基金项目
国家重点研发计划"水利工程建设与运行期遥感监测监督与风险预警"(编号:2021YFB3900603)资助. （编号:2021YFB3900603）
